Fault detection and diagnostics system utilizing service personnel feedback for improved accuracy

ABSTRACT

Systems and methods for fault detection and diagnosis (FDD) in a heating, ventilation and air conditioning (HVAC) system include a server identifying a fault and one or more predicted causes of the fault based on measurements of operational parameters from the HVAC system. The server also receives and utilizes information associated with the reported fault from service technicians who service the HVAC to correct the reported fault condition. The information includes details of the corrective measures successfully implemented by the technicians to correct the fault, and a determination of whether the server correctly identified the actual fault. The information is implemented by the server to improve the accuracy of the FDD algorithms based on measured parameters of the HVAC system.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of and priority to U.S. ProvisionalApplication Ser. No. 62/182,106 entitled “FAULT DETECTION ANDDIAGNOSTICS SYSTEM UTILIZING SERVICE PERSONNEL FEEDBACK FOR IMPROVEDACCURACY” and filed Jun. 19, 2015, and U.S. Provisional Application Ser.No. 62/182,119 entitled “SELF-LEARNING FAULT DETECTION FOR HVAC SYSTEMS”and filed Jun. 19, 2015, the entirety of each of which is herebyincorporated by reference herein for all purposes.

BACKGROUND

1. Technical Field

The present disclosure relates generally to fault detection anddiagnostics (FDD) for heating, ventilation and air conditioning (HVAC)systems. More specifically, this disclosure relates to incorporatingactual fault determination and their diagnoses into an FDD system toimprove predictions.

2. Background

Various methods and systems for detecting and diagnosing faults thatoccur in HVAC systems are known in the prior art. These systems oftenrely on manufacturer's data for fault detection and diagnosis (FDD), butmay also implement various algorithms for predicting a fault in aparticular system based on measured readings of operating parametersassociated with the equipment, for example. In some cases, diagnosticcapabilities may be embedded in the equipment itself.

However, there is no known system or method for capturing and analyzingthe success rate of an FDD system in predicting faults and diagnoses.There is also no known system for incorporating details of a servicedfault into the FDD system, after repairs have been made to resolve thereported fault.

SUMMARY

In one aspect, the present disclosure provides a method for faultdetection and diagnosis of an HVAC system. A server associated with theHVAC system identifies a fault in the system and determines one or morepredicted causes of the fault based on measurements of operationalparameters associated with the HVAC system. The server also receivesinformation associated with the fault that is based on observations fromone or more service technicians upon servicing the fault. Theinformation includes a corrective measure that was implemented tocorrect the fault, an indication of success or failure of the correctivemeasure, and an identification of an actual fault and a cause of theactual fault. The server then determines an accuracy of identifying theactual fault and the cause of the actual fault based on the informationreceived from the one or more service technicians.

In embodiments, the cause of the actual fault is determined based on thecorrective measure that successfully corrected the fault, as provided inthe information received from the service technician(s). Correctivemeasures reportedly implemented by the service technician may include,for example, adding a charge, removing a charge, replacing a component,correcting an airflow, or modifying a thermostat configuration in theheating, ventilation and air conditioning system.

In embodiments, the server transmits a notification of the faultidentified and instructions for correcting the fault, based on the oneor more predicted causes, to a mobile device accessible by one of theone or more service technicians. The server receives the information viaan app installed on the mobile device.

In embodiments, the fault and the one or more predicted causes may beidentified by applying a logic condition for determining whether thefault exists, wherein the logic condition associated with the fault isbased on the operational parameters applied by the logic condition and athreshold level for each of the operational parameters.

Embodiments of the method may further include analyzing the measurementsof the operational parameters, the threshold levels, the logiccondition, and the information associated with the fault, in response toa determination that the actual fault is different than the faultidentified by the server, or that the cause found by the servicetechnician is different than the server's predicted cause(s). From theanalysis, the server can then determine adjustments for improving theaccuracy of the fault detection and diagnosis, including adjustments toany combination of the logic condition, the operational parameters, andone or more threshold levels of the operational parameters toidentifying the fault and the one or more predicted causes.

In further embodiments, the server may then apply the adjustments to theat least one of the logic condition, the operational parameters, and theone or more threshold levels. Such adjustments may be appliedperiodically, for example, based on one of a predetermined time intervaland a predetermined number of instances of receiving the information. Inother embodiments, the adjustments may be automatically applied upondetermining what adjustments to the fault detection and diagnosis methodwill improve the accuracy.

In embodiments, the method may include storing a record of the faultidentified by the server, the one or more predicted causes, themeasurements of the operational parameters, and the informationassociated with the fault.

In further embodiments of the method, the server identifies the servicetechnician associated with each instance of the information received andstores a record of a number of instances associated with each of theservice technicians who provide the information.

In another aspect, the present disclosure provides a system for faultdetection and diagnosis in an HVAC system. The system includes a servercommunicably connected to a plurality of HVAC systems. The server isconfigured to identify a fault in one of the plurality of HVAC systemsand one or more predicted causes of the fault based on measurements ofoperational parameters associated with the HVAC system. The server isfurther configured to receive information associated with the faultbased on observations from one or more service technicians. Theinformation includes a corrective measure implemented to correct thefault, an indication of success or failure of the corrective measure,and an identification of an actual fault and a cause of the actualfault. An accuracy of identifying the actual fault and the cause of theactual fault is then determined by the server based on the informationreceived from the one or more service technicians.

In embodiments, the server is further configured to apply a logiccondition for determining whether the fault exists. The logic conditionassociated with the fault is based on the operational parameters and athreshold level for each of the operational parameters.

In further embodiments, the server is configured to analyze themeasurements of the operational parameters, the threshold levels, thelogic condition, and the information associated with the fault, inresponse to determining that the actual fault is different than thefault identified by the server and/or the cause reported by the servicetechnician is different than the predicted cause(s). The server is alsoconfigured to determine adjustments to one or more of the logiccondition, the operational parameters applied by the logic condition,and one or more threshold levels of the operational parameters toimprove the accuracy of the fault detection and diagnosis analysis.

In embodiments, the server may be further configured to apply theadjustments to the at least one of the logic condition, the operationalparameters, and the one or more threshold levels in response todetermining the adjustments for improving the accuracy.

In additional embodiments, the server is further configured to transmita notification of the fault identified by the server and instructionsfor correcting the fault based on the one or more predicted causes to amobile device accessible by the one or more service technicians; and toreceive the information via an app installed on the mobile device.

The server may be further configured, in embodiments, to store a recordof the fault, the one or more predicted causes, the measurements of theoperational parameters, and the information associated with the fault.

In additional embodiments, the server is further configured to store arecord of a number of instances information is received from each of theone or more service technicians.

In another aspect, the present disclosure provides a computer-readabledevice to store instructions that, when executed by a processing device,cause the processing device to perform operations. The operationsinclude identifying a fault in a heating, ventilation and airconditioning system and determining one or more predicted causes of thefault based on measurements of operational parameters associated withthe heating, ventilation and air conditioning system. The operationsalso include receiving information associated with the fault. Theinformation is based on observations from one or more servicetechnicians, and includes details of a corrective measure implemented tocorrect the fault, an indication of success or failure of the correctivemeasure, and an identification of an actual fault and a cause of theactual fault associated with the measurements of the operationalparameters. The operations further include determining an accuracy ofidentifying the actual fault and the cause of the actual fault based onthe information received from the one or more service technicians.

In embodiments, the operation of identifying the fault and the one ormore predicted causes includes applying a logic condition fordetermining whether the fault exists. The logic condition associatedwith the fault is based on the operational parameters applied by thelogic condition and a threshold level for each of the operationalparameters. The operations may further include analyzing themeasurements of the operational parameters, the threshold levels, thelogic condition, and the information associated with the fault, inresponse to determining that the actual fault reported is different thanthe fault identified by the server, or that the cause reported isdifferent than the one or more predicted causes. Based on the results ofthe analysis, the operations then further include determining theappropriate adjustments to at least one of the logic condition, theoperational parameters, and one or more threshold levels of theoperational parameters to improve the accuracy of identifying the faultand the one or more predicted causes.

In further embodiments, the operations include applying the adjustmentsto the at least one of the logic condition, the operational parameters,and the one or more threshold levels.

Other features and advantages will become apparent from the followingdescription of the preferred embodiments, taken in conjunction with theaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments of the disclosed system and method are describedherein with reference to the drawings wherein:

FIG. 1A is a schematic block diagram representation of an embodiment ofa system of the present disclosure;

FIG. 1B is a schematic block diagram representation of an embodiment ofa heating, ventilation and air conditioning system that is communicablycoupled to the embodiment of the system of FIG. 1;

FIG. 2 is a block diagram representation of data flow in an embodimentof a system of the present disclosure;

FIG. 3A is a block diagram representation of an embodiment of a methodof the present disclosure;

FIG. 3B is a block diagram representation of another embodiment of amethod of the present disclosure; and

FIG. 4 is a schematic block diagram representation of another embodimentof a system of the present disclosure.

The various aspects of the present disclosure mentioned above aredescribed in further detail with reference to the aforementioned figuresand the following detailed description of exemplary embodiments.

DETAILED DESCRIPTION

The present disclosure is directed to a method and system for faultdetection and diagnosis in heating, ventilation and air conditioningsystems. Embodiments of the method and system incorporate feedback fromfield service technicians to improve the accuracy of algorithms used fordetecting and diagnosing faults in the HVAC systems. The cooperation ofthe various field service technicians in providing such feedback data isalso preferably tracked so that rewards may be granted as an incentivefor increased participation by the field service technicians.

Particular illustrative embodiments of the present disclosure aredescribed hereinbelow with reference to the accompanying drawings;however, the disclosed embodiments are merely examples of thedisclosure, which may be embodied in various forms. Well-known functionsor constructions and repetitive matter are not described in detail toavoid obscuring the present disclosure in unnecessary or redundantdetail. Therefore, specific structural and functional details disclosedherein are not to be interpreted as limiting, but merely as a basis forthe claims and as a representative basis for teaching one skilled in theart to variously employ the present disclosure in virtually anyappropriately detailed structure. In this description, as well as in thedrawings, like-referenced numbers represent elements which may performthe same, similar, or equivalent functions. The word “exemplary” is usedherein to mean “serving as an example, instance, or illustration.” Anyembodiment described herein as “exemplary” is not necessarily to beconstrued as preferred or advantageous over other embodiments. The word“example” may be used interchangeably with the term “exemplary.”

The present disclosure may be described herein in terms of functionalblock components, code listings, optional selections, page displays, andvarious processing steps. It should be appreciated that such functionalblocks may be realized by any number of hardware and/or softwarecomponents configured to perform the specified functions. For example,the present disclosure may employ various integrated circuit components,e.g., memory elements, processing elements, logic elements, look-uptables, and the like, which may carry out a variety of functions underthe control of one or more microprocessors or other control devices.

Referring to an embodiment of a system 10 of the present disclosure asshown in FIG. 1A, for example, in various embodiments, the hardwareand/or software components for implementing one or more of thefunctional blocks or method steps may be implemented on one or moreserver(s) 12 accessing data from a plurality of HVAC systems 16, ordistributed between any combination of one or more server(s) 12 and auser device 14 operably connected to the one or more server(s) 12.

The user devices of the present disclosure may be mobile devices, suchas a smart phone or tablet, including an app installed for enablingservice technicians to communicate information obtained from servicing areported fault in an HVAC system. In embodiments, user devices may alsoinclude any other suitable device, including a computer, laptop, and soon, for entry and transmission of the information via a web-basedinterface, for example.

Similarly, the software elements of the present disclosure may beimplemented with any programming or scripting language such as C, C++,C#, Java, COBOL, assembler, PERL, Python, PHP, or the like, with thevarious algorithms being implemented with any combination of datastructures, objects, processes, routines or other programming elements.The object code created may be executed by any device, on a variety ofoperating systems, including without limitation Apple OSX®, Apple iOS®,Google Android®, HP WebOS®, Linux, UNIX®, Microsoft Windows®, and/orMicrosoft Windows Mobile®.

It should be appreciated that the particular implementations describedherein are illustrative of the disclosure and its best mode and are notintended to otherwise limit the scope of the present disclosure in anyway. Examples are presented herein which may include sample data itemswhich are intended as examples and are not to be construed as limiting.Indeed, for the sake of brevity, conventional data networking,application development and other functional aspects of the systems (andcomponents of the individual operating components of the systems) maynot be described in detail herein. It should be noted that manyalternative or additional functional relationships or physical orvirtual connections may be present in a practical electronic system orapparatus.

As will be appreciated by one of ordinary skill in the art, the presentdisclosure may be embodied as a method, a device, e.g., a server device,configured to implement the methods disclosed herein, and/or a computerprogram product. Accordingly, the present disclosure may take the formof an entirely software embodiment, an entirely hardware embodiment, oran embodiment combining aspects of both software and hardware.Furthermore, the present disclosure may take the form of a computerprogram product on a computer-readable storage medium havingcomputer-readable program code means embodied in the storage medium. Anysuitable computer-readable storage medium may be utilized, includinghard disks, CD-ROM, DVD-ROM, optical storage devices, magnetic storagedevices, semiconductor storage devices (e.g., flash memory, USB thumbdrives) and/or the like.

Computer program instructions embodying the present disclosure may alsobe stored in a computer-readable memory that can direct a computer orother programmable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablememory produce an article of manufacture, including instruction means,that implement the function specified in the description or flowchartblock(s). The computer program instructions may also be loaded onto acomputer or other programmable data processing apparatus to cause aseries of operational steps to be performed on the computer or otherprogrammable apparatus to produce a computer-implemented process suchthat the instructions that execute on the computer or other programmableapparatus provide steps for implementing the functions specified in thepresent disclosure.

Referring again to FIG. 1A, for example, in one embodiment, the server12 includes at least a processing device or devices 22, memory includingcomputer readable memory or storage 24 for storage of software,instructions, or executable code, which when executed by the processingdevice(s) 22 causes the processing device(s) 22 to perform methods ormethod steps of the present disclosure, which may be embodied at leastin part in programming instructions 26 stored on or retrievable by theserver 12. It will be appreciated by those of ordinary skill in the artthat such components 22, 24 and programming instructions 26 forperforming the methods or method steps of the present disclosure may bealso be distributed among various devices, which may include userdevices 14, such as computers, laptops, mobile devices, phones, tablets,and so on, and may also, in embodiments, include programmable logicinstalled in components of the HVAC system(s) 16.

One skilled in the art will also appreciate that, for security reasons,any databases, systems, or components of the present disclosure mayconsist of any combination of databases or components at a singlelocation or at multiple locations, wherein each database or systemincludes any of various suitable security features, such as firewalls,access codes, encryption, de-encryption, compression, decompression,and/or the like.

The disclosed systems and/or methods may be embodied, at least in part,in application software that may be downloaded, in whole or in part,from either a public or private website or an application store (“appstore”) to a mobile device. In another embodiment, the disclosed systemand method may be included in the mobile device firmware, hardware,and/or software. In another embodiment, the disclosed systems and/ormethods may be embodied, at least in part, in application softwareexecuting within a webserver to provide a web-based interface to thedescribed functionality.

In yet other embodiments, all or part of the disclosed systems and/ormethods may be provided as one or more callable modules, an applicationprogramming interface (e.g., an API), a source library, an objectlibrary, a plug-in or snap-in, a dynamic link library (e.g., DLL), orany software architecture capable of providing the functionalitydisclosed herein.

The term “sensors” as used herein refers collectively to both sensorsand transducers as commonly used in the art, and includes sensorsassociated with a particular piece of equipment and/or control unit orthermostat in the HVAC system, such as a temperature sensor in athermostat. Sensors may be located on or operably connected to certainHVAC equipment. Other sensors co-located with an HVAC system may, or maynot be operably connected to HVAC equipment, but may still be used inaccordance with methods of the present disclosure to analyze the datacollected for detecting and diagnosing a fault in the HVAC system.Examples of sensors from which data may be collected for analysis inaccordance with the present disclosure include, but are not limited to,temperature, humidity, pressure, occupancy, smoke, light, motion,security sensors, and so on. Data that may be acquired from sensorsand/or equipment (which may include sensors or embedded controllers)includes, but is not limited to, measured data readings (e.g.,temperature, pressure, humidity, and so on), set point (e.g., auser-defined temperature setting), current state (e.g., an “occupied” or“unoccupied” reading from an occupancy sensor), and modes of operation(e.g., heat or cool mode of a thermostat).

Referring to FIG. 1A, an embodiment of a system 10 of the presentdisclosure for detecting and diagnosing faults in a heating, ventilationand air conditioning (HVAC) system is shown. The system 10 includes aserver 12 communicably coupled to a plurality of HVAC systems 16, viathe Internet 28, for example, and specially configured to implement andexecute the methods of the present disclosure. The server 12 may also beconfigured to establish communications with a plurality of user devices14 utilized by field service technicians and to send variousnotifications and instructions to the user devices 14 regarding anyfaults detected in the HVAC systems 16 in accordance with the presentdisclosure. In embodiments described further hereinbelow, the userdevices 14 are enabled to receive such notifications from the server 12and to respond by sending information regarding the fault reported bythe server 12. In embodiments, a database 30 is communicatively coupledto the server 12 for storing such information and fault data. Thedatabase 30, in embodiments, may also be accessible to the servicetechnicians' devices 14, via the Internet 28, for example, for storingthe feedback information from the service technicians.

Referring to FIG. 1B, by way of example, an HVAC system 16 a typicallyincludes a thermostat 18 and may include various additional controlunits 20, each of which may be operable via a touch-screen panel as wellas via a separate user device operated by a homeowner or systemoperator. Additional equipment in the HVAC system 16 a may include, butis not limited to, furnaces and heating equipment, air conditioners,filters, air purifiers, ventilation equipment, chillers, pumps, and airhandlers.

Equipment in the HVAC system 16 a may include both indoor 40 and outdoorequipment 42, each of which may include sensors 32 operably connected toand/or embedded in the equipment. Some equipment may include embeddedlogic controllers 34 for monitoring and controlling operation.

Additional sensors 36 may be co-located with the system 16 a and may ormay not be operably connected to equipment within the HVAC system 16 a.Such sensors 36 may include, but are not limited to, occupancy, smoke,light, motion, security, humidity, pressure sensors, and so on. Inaccordance with the present disclosure, data from these sensors 32, 36and logic controllers 34 may be collected, stored, and analyzed by theserver 12 to assess current operational parameters and trends in theequipment and HVAC system 16 a, for detection and diagnosis of faults inaccordance with predetermined logic conditions.

As will be described further below, various types of data are generatedby the sensors associated with the plurality of HVAC systems 16.Referring still to FIG. 1B, embodiments of the HVAC system 16 a mayinclude an electronic gathering device 44 configured to acquire datafrom any components associated with the system 16, including the controlunit(s) 20, thermostat 18, both indoor 40 and outdoor equipment 42, andassociated sensors 32, 36, and forward the data via the Internet 28, forexample, to the server 12 for processing.

The electronic gathering device 44 is operably connected to the server12 for transmission of the acquired data thereto and configured fortransmitting the data by any suitable connection, either wired orwireless 46, of any appropriate type, including but not limited to WiFi,cellular, Ethernet, POTS via modem, and so on.

In some embodiments, the thermostat 18 of the HVAC system is operablyconnected to the data gathering device 44, has Internet connectivity 48,e.g., WiFi, Ethernet, and so on, and can provide the data pathway fromthe electronic data gathering device 44 to the central remote server 22via the Internet 28. Any combination of the thermostat 18 and theoptional electronic data gathering device 44, or any other method knownin the art, may be used to transmit the data, including measurements ofvarious operating parameters, from the HVAC systems 16 to the server 12for fault detection and diagnosis.

FIG. 2 illustrates a flow of data between an HVAC system 16 a, a servicetechnician's device 14, which may be a mobile device, and an embodimentof a server 12 in accordance with the present disclosure. The measureddata 50 from the sensors 32, 36, and the like associated with the HVACsystem 16 a may include continuous data 52 and event data 54. Themeasured data is collected and transmitted to the server 12 formonitoring and analysis and may also be stored in the database 30. Thedata 50 can include continuous measurements 52 of various operationalparameters, such as, but not limited to, indoor temperature, outdoortemperature, pressure, system modes, setpoints, indoor humidity,compressor power, and so on. The data 50 may also include discretesystem operation events 54, such as, but not limited to, calls forcooling operation, recorded events of a compressor turned on or off,changes in setpoints and/or system modes, and any other event that istriggered, for example, by a change in a system operating condition. Themeasurements of the operational parameters that are stored in thedatabase 30, therefore, can be any combination of continuously acquireddata 52 and discrete, event data 54.

The server 12 detects and diagnoses faults based on the measurements 50of the operational parameters acquired from the HVAC system 16 a asdescribed further hereinbelow. If a fault is detected, a notification ofthe fault with instructions 56 may be sent by the server 12 to a userdevice 14 accessible by a service technician. Upon correction of thefault, the service technician provides information 58 associated withthe correction via the user device 14 to the server 12, which may alsobe stored in the database 30 by the server 12, or directly to thedatabase 30. In embodiments, the database 30 may include records 60 thatinclude all faults detected by the server 12, along with theFDD-generated fault diagnoses, the measured dataset 50 to which each FDDdiagnosis was applied, and the feedback information provided via theuser device 14, including whether or not the FDD fault diagnosisprovided by the server 12 was correct. These records 60 are used by theserver 12, or in other embodiments of the present disclosure, by athird-party server, to optimize the fault detection and diagnosislogistics as described further herein.

FIG. 3A illustrates embodiments of a method 70 in accordance with thepresent disclosure to detect and diagnose faults in an HVAC system thatis operably connected to a server 12 as described above. Referring alsoto FIG. 2, in accordance with the method 70, the server identifies, at72, a fault in an HVAC system 16 and determines, at 74, one or morepredicted causes of the fault based on the measurements of operationalparameters 50 that are passed to the server 12 from the HVAC system 16.In embodiments, the server transmits, at 75, a fault notification andinstructions for correcting the fault to a service technician's mobiledevice. The server 12 receives information associated with the fault at76 from the service technician to which the fault notification wasissued and also accumulates information from other service techniciansbased on their observations in servicing the same reported fault in pastservice calls. The information reported by the service techniciansincludes the corrective measure(s) that were implemented to successfullycorrect the fault. The information may also include a listing ofcorrective measure(s) that were implemented without success, includingany measures that the service technician was originally instructed toimplement to correct a suspected cause of the fault, as diagnosed by theserver 12.

For example, the service technician may determine the actual cause ofthe fault by making suggested changes to correct the operational error.The service technician may have attempted certain corrections that wereprovided in the instructions along with the fault notification, or maytry other changes based on his or her prior experience. Such correctivemeasures may include, for example, adding a charge, removing a charge,replacing a component, correcting an airflow, or modifying a thermostatconfiguration in the heating, ventilation and air conditioning system.In embodiments, the information provided at 76 by the servicetechnicians preferably includes this level of detail for implementationby the FDD server 12.

By comparing the information from the service technicians with the faultand predicted cause that the server determined from the measuredparameters, the server, at 78, determines an accuracy of the algorithmand parameters used to identify and diagnose the fault.

In additional embodiments, the server, at 80, stores a record of thefault identified by the server and the one or more predicted causes, theaccuracy of detecting and diagnosing the actual fault, the measuredoperational parameters used to detect and diagnose, and the informationabout the actual fault and causes received from the service technicians.

In embodiments, at 82, the server 12 also identifies the servicetechnician associated with each instance of information received andtracks the number of instances associated with each service technician.In this way, a reward system may be implemented to incentivize theservice technicians to provide helpful information after each servicecall.

Referring now to FIG. 3B, in embodiments, the information associatedwith a fault is collected from service technicians, at 88, via theservice technicians' user devices. The information may be collected by athird-party server 112, as shown in FIG. 4, or by an FDD server 12, asshown in FIG. 1A. The method includes the server 112, or server 12,applying a logic condition, at 90, to determine whether or not a faultexists and to identify the fault. The logic condition associated withthe fault is based on measurements of particular operational parameters,and a predetermined threshold level for each of the operationalparameters.

Referring to FIG. 4, in embodiments of a system of the presentdisclosure utilizing third-party server 112, server 112 includes atleast a processing device or devices 122, memory including computerreadable memory or storage 124 for storage of software, instructions, orexecutable code, which when executed by the processing device(s) 122causes the processing device(s) 122 to perform methods or method stepsof the present disclosure, including analysis of the information aboutthe actual faults reported, and the predictions provided by the server112. The method steps may be embodied at least in part in programminginstructions 126 stored on or retrievable by the server 112. Inembodiments, a database 130 is also communicatively coupled to theserver 112 for storing such information and fault data for analysis. Inthe system of FIG. 4, the analysis of the accuracy of the FDD based onthe technicians' feedback, as described further below, is performed bythird-party server 112, and the recommended adjustments to the FDDanalysis are stored for either manual, or automatic, integration into anFDD server in accordance with the present disclosure.

Various methods of fault detection and diagnosis are known in the artand can be applied to the methods of the present disclosure. Inembodiments of the present disclosure, logic conditions are establishedand applied by the server 12 for identifying faults based onmeasurements of the operational parameters. For example, a thresholdvalue may be predetermined for a particular operational parameter, and alogic condition established that determines a particular fault exists,under certain system operating conditions, when a particular operationalparameter either exceeds, or drops below, the predetermined thresholdvalue. In other embodiments, the logic condition determines theexistence of a fault based on an analysis of measurements of apredetermined set of operational parameters and their predeterminedthreshold values. An accuracy of an FDD will depend on the logiccondition applied, the set of operational parameters selected by thelogic condition to identify a fault, and the predetermined thresholdvalues for those operational parameters.

The information provided by the service technicians can help optimizethe logic condition for defining a fault, for example, by determiningwhether the optimal combination of operational parameters are beingapplied to predict that a fault exists, as well as to optimize thethreshold values and algorithms used to determine which fault out of allpossible faults for a particular HVAC system exists. In particular, ifthe information provided by the service technicians indicates that thereis an error in the logic used to predict a fault in a particularinstance, for example, because the actual fault and/or cause were foundto differ from that predicted by the server, further analysis iswarranted. Accordingly, embodiments of the method further includeanalyzing, at 92, the measurements of the operational parameters, thethreshold levels, the logic condition, and the information, anddetermining, at 94, adjustments to the logic condition and/or theoperational parameters, and/or one or more threshold levels of theoperational parameters to improve the accuracy of the FDD by the server12. These adjustments may be determined and stored by the third-partyserver 112 for manual, or automated, importation to an FDD server 12, asshown in FIG. 4, for example, or the analysis, determination ofadjustments, as well as the application, at 96, of the adjustments maybe performed in whole, or in part, by the FDD server 12, as shown inFIG. 1A, for example.

In embodiments, the adjustments determined at 94 are applied to theserver 12 at 96 for improving the accuracy of the fault detection anddiagnosis. Accordingly, as more information is received from the servicetechnicians, the accuracy of the FDD by the server 12 is furtherimproved. In additional embodiments, the server 12 performs the applyingstep periodically, at 98, based on a predetermined time interval or on apredetermined number of instances of receiving the information.

Aspects

It is noted that any of aspects 1-9 below can be combined with eachother in any combination and combined with any of aspects 10-17, or anyof aspects 18-20. Any of aspects 10-20 can be combined with each otherin any combination.

Aspect 1. A method of detecting and diagnosing faults detection in aheating, ventilation and air conditioning system, the method comprising:identifying, by a server, a fault in a heating, ventilation and airconditioning system and determining, by the server, one or morepredicted causes of the fault based on measurements of operationalparameters associated with the heating, ventilation and air conditioningsystem; receiving, by the server, information associated with the fault,the information being based on observations from one or more servicetechnicians, the information including a corrective measure implementedto correct the fault, an indication of success or failure of thecorrective measure, and an identification of an actual fault and a causeof the actual fault; and determining, by the server, an accuracy ofidentifying the actual fault and the cause of the actual fault based onthe information received from the one or more service technicians.

Aspect 2. The method according to Aspect 1, further comprisingtransmitting, by the server, a notification of the fault identified bythe server and instructions for correcting the fault based on the one ormore predicted causes to a mobile device accessible by one of the one ormore service technicians, the server receiving the information via anapp installed on the mobile device.

Aspect 3. The method according to any of Aspects 1-2, furthercomprising: storing, by the server, a record of the fault identified bythe server, the one or more predicted causes, the measurements of theoperational parameters, and the information associated with the fault.

Aspect 4. The method according to any of Aspects 1-3, whereinidentifying the fault and the one or more predicted causes includesapplying a logic condition for determining whether the fault exists,wherein the logic condition associated with the fault is based on theoperational parameters applied by the logic condition and a thresholdlevel for each of the operational parameters.

Aspect 5. The method according to any of Aspects 1-4, further comprisinganalyzing, by the server, the measurements of the operationalparameters, threshold levels for each of the operational parameters, alogic condition for determining whether the fault exists, and theinformation associated with the fault, in response to one of the actualfault being different than the fault and the cause being different thanthe one or more predicted causes; and determining, by the server,adjustments to at least one of the logic condition, the operationalparameters, and one or more threshold levels of the operationalparameters to improve the accuracy of identifying the fault and the oneor more predicted causes based on results of the analyzing step.

Aspect 6. The method according to any of Aspect 1-5, further comprising:applying, by the server, adjustments to the at least one of the logiccondition, the operational parameters, and the one or more thresholdlevels based on results of the analyzing step of Aspect 5.

Aspect 7. The method according to any of Aspects 1-6, further comprisingapplying adjustments to the at least one of the logic condition, theoperational parameters, and the one or more threshold levels based onresults of the analyzing step of Aspect 5 periodically based on one of apredetermined time interval and a predetermined number of instances ofreceiving the information.

Aspect 8. The method according to any of Aspects 1-7, wherein the causeof the actual fault is determined based on the information including thecorrective measure that successfully corrected the fault.

Aspect 9. The method according to any of Aspects 1-8, wherein thecorrective measure includes one of adding a charge, removing a charge,replacing a component, correcting an airflow, and modifying a thermostatconfiguration in the heating, ventilation and air conditioning system.

Aspect 10. The method according to any of Aspects 1-9, furthercomprising: identifying, by the server, the one of the servicetechnicians associated with each instance of the information received;and storing, by the server, a record of a number of instances associatedwith each of the one or more service technicians.

Aspect 11. A system for fault detection and diagnosis in a heating,ventilation and air conditioning system, the system comprising: a servercommunicably connected to a plurality of heating, ventilation and airconditioning systems, wherein the server is configured to: identify afault in one of the plurality of heating, ventilation and airconditioning systems and one or more predicted causes of the fault basedon measurements of operational parameters associated with the one of theplurality of heating, ventilation and air conditioning systems; receiveinformation associated with the fault based on observations from one ormore service technicians, the information including a corrective measureimplemented to correct the fault, an indication of success or failure ofthe corrective measure, and an identification of an actual fault and acause of the actual fault; and determine an accuracy of identifying theactual fault and the cause of the actual fault based on the informationreceived from the one or more service technicians.

Aspect 12. The system according to Aspect 11, wherein the server isfurther configured to: transmit a notification of the fault identifiedby the server and instructions for correcting the fault based on the oneor more predicted causes to a mobile device accessible by the one ormore service technicians; and receive the information via an appinstalled on the mobile device.

Aspect 13. The system according to any of Aspects 11-12, wherein theserver is further configured to: store a record of the fault, the one ormore predicted causes, the measurements of the operational parameters,and the information associated with the fault.

Aspect 14. The system according to any of Aspects 11-13, wherein theserver is further configured to apply a logic condition for determiningwhether the fault exists, wherein the logic condition associated withthe fault is based on the operational parameters and a threshold levelfor each of the operational parameters.

Aspect 15. The system according to any of Aspects 11-14, the serverbeing further configured to: analyze the measurements of the operationalparameters, the threshold levels for each of the operational parameters,the logic condition for determining whether the fault exists, and theinformation associated with the fault, in response to one of the actualfault being different than the fault and the cause being different thanthe one or more predicted causes; and determine adjustments to at leastone of the logic condition, the operational parameters applied by thelogic condition, and one or more threshold levels of the operationalparameters to improve the accuracy of identifying the fault and the oneor more predicted causes based on results of the analysis.

Aspect 16. The system according to any of Aspects 11-15, wherein theserver is further configured to: apply adjustments to at least one ofthe logic condition, the operational parameters, and the one or morethreshold levels of the operational parameters in response todetermining the adjustments.

Aspect 17. The system according to any of Aspects 11-16, wherein theserver is further configured to identify the one of the servicetechnicians associated with each instance of the information received;and store a record of a number of instances associated with each of theone or more service technicians.

Aspect 18. A computer-readable device to store instructions that, whenexecuted by a processing device, cause the processing device to performoperations comprising: identifying a fault in a heating, ventilation andair conditioning system and determining one or more predicted causes ofthe fault based on measurements of operational parameters associatedwith the heating, ventilation and air conditioning system; receivinginformation associated with the fault, the information being based onobservations from one or more service technicians, the informationincluding a corrective measure implemented to correct the fault, anindication of success or failure of the corrective measure, and anidentification of an actual fault and a cause of the actual fault; anddetermining an accuracy of identifying the actual fault and the cause ofthe actual fault based on the information received from the one or moreservice technicians.

Aspect 19. The computer-readable device according to Aspect 18, whereinidentifying the fault and the one or more predicted causes includesapplying a logic condition for determining whether the fault exists,wherein the logic condition associated with the fault is based on theoperational parameters applied by the logic condition and a thresholdlevel for each of the operational parameters, the operations furthercomprising: analyzing the measurements of the operational parameters,the threshold levels, the logic condition, and the informationassociated with the fault, in response to one of the actual fault beingdifferent than the fault and the cause being different than the one ormore predicted causes; and determining adjustments to at least one ofthe logic condition, the operational parameters, and one or morethreshold levels of the operational parameters to improve the accuracyof identifying the fault and the one or more predicted causes based onresults of the analyzing step.

Aspect 20. The computer-readable device according to any of Aspects18-19, the operations further comprising: applying adjustments to the atleast one of the logic condition, the operational parameters, and theone or more threshold levels in response to analyzing and determiningthe adjustments according to Aspect 19.

Particular embodiments of the present disclosure have been describedherein, however, it is to be understood that the disclosed embodimentsare merely examples of the disclosure, which may be embodied in variousforms. Well-known functions or constructions are not described in detailto avoid obscuring the present disclosure in unnecessary detail.Therefore, specific structural and functional details disclosed hereinare not to be interpreted as limiting, but merely as a basis for theclaims and as a representative basis for teaching one skilled in the artto variously employ the present disclosure in any appropriately detailedstructure.

What is claimed is:
 1. A method of detecting and diagnosing faults in aheating, ventilation and air conditioning system, the method comprising:identifying, by a server, a fault in a heating, ventilation and airconditioning system and determining, by the server, one or morepredicted causes of the fault based on measurements of operationalparameters associated with the heating, ventilation and air conditioningsystem; receiving, by the server, information associated with the fault,the information being based on observations from one or more servicetechnicians, the information including a corrective measure implementedto correct the fault, an indication of success or failure of thecorrective measure, and an identification of an actual fault and a causeof the actual fault; and determining, by the server, an accuracy ofidentifying the actual fault and the cause of the actual fault based onthe information received from the one or more service technicians. 2.The method of claim 1, further comprising: transmitting, by the server,a notification of the fault identified by the server and instructionsfor correcting the fault based on the one or more predicted causes to amobile device accessible by one of the one or more service technicians,the server receiving the information via an app installed on the mobiledevice.
 3. The method of claim 1, further comprising: storing, by theserver, a record of the fault identified by the server, the one or morepredicted causes, the measurements of the operational parameters, andthe information associated with the fault.
 4. The method of claim 1,wherein identifying the fault and the one or more predicted causesincludes applying a logic condition for determining whether the faultexists, wherein the logic condition associated with the fault is basedon the operational parameters applied by the logic condition and athreshold level for each of the operational parameters.
 5. The method ofclaim 4, further comprising: analyzing, by the server, the measurementsof the operational parameters, the threshold levels, the logiccondition, and the information associated with the fault, in response toone of the actual fault being different than the fault and the causebeing different than the one or more predicted causes; and determining,by the server, adjustments to at least one of the logic condition, theoperational parameters, and one or more threshold levels of theoperational parameters to improve the accuracy of identifying the faultand the one or more predicted causes based on results of the analyzingstep.
 6. The method of claim 5, further comprising applying, by theserver, the adjustments to the at least one of the logic condition, theoperational parameters, and the one or more threshold levels in responseto determining the adjustments.
 7. The method of claim 6, furthercomprising performing the applying step periodically based on one of apredetermined time interval and a predetermined number of instances ofreceiving the information.
 8. The method of claim 1, wherein the causeof the actual fault is determined based on the information including thecorrective measure that successfully corrected the fault.
 9. The methodof claim 8, wherein the corrective measure includes one of adding acharge, removing a charge, replacing a component, correcting an airflow,and modifying a thermostat configuration in the heating, ventilation andair conditioning system.
 10. The method of claim 1, further comprising:identifying, by the server, the one of the service techniciansassociated with each instance of the information received; and storing,by the server, a record of a number of instances associated with each ofthe one or more service technicians.
 11. A system for fault detectionand diagnosis in a heating, ventilation and air conditioning system, thesystem comprising a server communicably connected to a plurality ofheating, ventilation and air conditioning systems, wherein the server isconfigured to: identify a fault in one of the plurality of heating,ventilation and air conditioning systems and one or more predictedcauses of the fault based on measurements of operational parametersassociated with the one of the plurality of heating, ventilation and airconditioning systems; receive information associated with the faultbased on observations from one or more service technicians, theinformation including a corrective measure implemented to correct thefault, an indication of success or failure of the corrective measure,and an identification of an actual fault and a cause of the actualfault; and determine an accuracy of identifying the actual fault and thecause of the actual fault based on the information received from the oneor more service technicians.
 12. The system of claim 11, wherein theserver is further configured to: transmit a notification of the faultidentified by the server and instructions for correcting the fault basedon the one or more predicted causes to a mobile device accessible by theone or more service technicians; and receive the information via an appinstalled on the mobile device.
 13. The system of claim 11, wherein theserver is further configured to: store a record of the fault, the one ormore predicted causes, the measurements of the operational parameters,and the information associated with the fault.
 14. The system of claim11, wherein the server is further configured to: apply a logic conditionfor determining whether the fault exists, wherein the logic conditionassociated with the fault is based on the operational parameters and athreshold level for each of the operational parameters.
 15. The systemof claim 14, the server being further configured to: analyze themeasurements of the operational parameters, the threshold levels, thelogic condition, and the information associated with the fault, inresponse to one of the actual fault being different than the fault andthe cause being different than the one or more predicted causes; anddetermine adjustments to at least one of the logic condition, theoperational parameters applied by the logic condition, and one or morethreshold levels of the operational parameters to improve the accuracyof identifying the fault and the one or more predicted causes based onresults of the analysis.
 16. The system of claim 15, wherein the serveris further configured to apply the adjustments to the at least one ofthe logic condition, the operational parameters, and the one or morethreshold levels in response to determining the adjustments.
 17. Thesystem of claim 11, wherein the server is further configured to:identify the one of the service technicians associated with eachinstance of the information received; and store a record of a number ofinstances associated with each of the one or more service technicians.18. Non-transitory computer-readable media storing instructions that,when executed by a processing device, cause the processing device toperform operations comprising: identifying a fault in a heating,ventilation and air conditioning system and determining one or morepredicted causes of the fault based on measurements of operationalparameters associated with the heating, ventilation and air conditioningsystem; receiving information associated with the fault, the informationbeing based on observations from one or more service technicians, theinformation including a corrective measure implemented to correct thefault, an indication of success or failure of the corrective measure,and an identification of an actual fault and a cause of the actualfault; and determining an accuracy of identifying the actual fault andthe cause of the actual fault based on the information received from theone or more service technicians.
 19. The non-transitorycomputer-readable media of claim 18, wherein identifying the fault andthe one or more predicted causes includes applying a logic condition fordetermining whether the fault exists, wherein the logic conditionassociated with the fault is based on the operational parameters appliedby the logic condition and a threshold level for each of the operationalparameters, the operations further comprising: analyzing themeasurements of the operational parameters, the threshold levels, thelogic condition, and the information associated with the fault, inresponse to one of the actual fault being different than the fault andthe cause being different than the one or more predicted causes; anddetermining adjustments to at least one of the logic condition, theoperational parameters, and one or more threshold levels of theoperational parameters to improve the accuracy of identifying the faultand the one or more predicted causes based on results of the analyzingstep.
 20. The non-transitory computer-readable media of claim 19, theoperations further comprising applying the adjustments to the at leastone of the logic condition, the operational parameters, and the one ormore threshold levels in response to determining the adjustments.